自保护技术作为自愈技术的一种,能够使系统在环境或工况条件变化的干扰下以较高可靠性运行。本文构建了一个新的具有相依主要部件和辅助部件的系统可靠性模型,其中主要部件的退化速率与工作中的辅助部件的数量有关。此外,基于定期检测

For artificial systems, the rising cost and inaccessible scenes for maintenance have increased the need of self-healing, which intends to give systems the ability to heal the damage and faults without external intervention like living organisms. Although self-healing techniques have been widely studied and applied in many engineering systems, reliability research for such systems is limited. Besides, the self-healing ability of artificial systems is generally derived from self-healing resources embedded in the system, while the limitations of embedded resources have less been considered in related research. To fill the research gap, in this paper we consider systems operating under shock environments with limited self-healing resources. Two self-healing policies are designed for allocating the limited resources and enhancing the system reliability. Under different policies, new reliability models are developed and a recursive method is proposed to evaluate the system reliability. Further, some new indexes are introduced and derived for evaluating the performance of the self-healing policies. Based on the new indexes, numerical examples are presented in the end to compare the two policies. © 2023

In many engineering systems, aside from the main component fulfilling the essential functions, a number of auxiliary components are configured to protect the main component and improve the reliability of the system. In actual operation, the failure or state change of the auxiliary components may affect the reliability both the main component and the remaining operational auxiliary components. However, the structure and dependence between the auxiliary components has been ignored in the existing studies. To fill this gap, we consider a system with a main component and a protective auxiliary subsystem. The latter is a load-sharing k out-of -n system, that is, there is dependence between the auxiliary components. For such a system, an opportunistic inspection and preventive maintenance strategy is proposed. Then, we derive the system reliability using the Laplace transforms and the matrix method. The long-run average cost of the system is then derived, based on which the optimal maintenance problem is formulated and solved by an enumeration method. A numerical example, together with sensitivity studies of some model parameters, shows how the evolution of the parameters influences the optimal maintenance strategy. Finally, the model is extended by introducing periodic inspection and preventive maintenance strategy for main component, and the two strategies are compared.

随着科学技术的进步与发展,人们对产品的要求越来越高,不仅希望产品能够满足其功能需求,而且希望产品的寿命越长越好或是在使用期间出现故障的次数越少越好。对产品寿命进行可靠性建模与分析,能有效预测产品的寿命演化规律,进一步地,所建立的可靠性模型也能为产品的维修策略提供依据和保障。在实际中,很多系统（或产品）会同时受到多种失效模式的影响,其中退化失效（由系统本身的退化导致）和突发失效（由环境中的随机冲击导致）较为常见,这两种失效模式之间相互竞争,系统的失效由最早出现的失效模式导致,这类系统被称为竞争失效系统（或竞争风险系统）。现实生活中,竞争失效系统颇为常见,如电池、微机电、电力系统等,这类系统一旦发生故障,则会造成较大的经济损失,因此,对竞争失效系统进行可靠性建模与维修策略研究具有重要的理论意义与实用价值。本文以竞争失效系统为研究对象,从可靠性建模和维修策略两个维度展开。一方面,运用基于退化的可靠性建模方法,冲击理论,Copula方法等对竞争失效系统进行可靠性建模与分析;另一方面,基于视情维修策略,采用延迟时间模型（Delay time model）,比例役龄消减模型（Proportional age reduction model）等方法对竞争失效系统进行维修建模。首先,在考虑失效模式之间相关性的基础上对竞争失效系统进行了可靠性建模与分析。本文将随机冲击分为致命冲击（Fatal shock）、一般冲击（General shock）和微小冲击（Small shock）三类,基于此,对高可靠长寿命的竞争失效系统进行了可靠性建模。在构建可靠性模型时,假设微小冲击不会对系统产生任何影响,一般冲击不仅会导致退化过程产生突然的退化增量,还可能导致系统的退化率增大,而致命冲击则会导致系统突发失效。此外,采用Copula方法处理多个退化过程之间的相关性问题。最后通过数值算例验证了所建可靠性模型的有效性和准确性。其次,基于视情维修策略对竞争失效系统进行了维修建模。可靠性建模与分析有助于评估系统可靠性,而有效的维修措施则能增大系统在使用期间的可用度。本文假设竞争失效系统在失效之前具有相同的性能水平,即系统只有正常和失效两种工作状态,基于此前提假设,采用视情维修策略对竞争失效系统进行了维修建模,构建了系统的期望成本率函数,并以串联系统为验证对象,展示了所构建维修模型的有效性。然后,对多状态竞争失效系统进行了维修建模。在工程实际中,系统在不同的工作时段内可能具有不同的性能水平,若将每一性能水平看作一个系统状态,则系统可被离散为多个状态。本文针对三状态竞争失效系统（正常、缺陷和失效）,并在完全检测（Perfect inspection）的基础上,对系统进行了视情维修建模。最后以电容器组为例,验证了所构建模型的适用性。再次,考虑了不完全检测情形,对多状态竞争失效系统进行了维修建模。由于检测设备以及检测人员技术水平的局限性,检测存在一定的误差。本文假设针对缺陷的检测是不完全的,即不完全检测（Imperfect inspection）,并基于视情维修策略,对多状态竞争失效系统进行了维修性建模。最后通过数值算例验证了维修模型的适用性和有效性。最后,在同时考虑不完全检测和不完全维修（Imperfect maintenance）的基础上,对多状态竞争失效系统进行了维修建模。当检测识别出系统缺陷时,就对系统进行预防性更换,通常会产生较高的成本。在实际中,一些经济有效的维修活动便可消除系统缺陷。然而,维修通常只能使系统恢复至“如新”和“如旧”之间的某一状态,即维修是不完全的。本文在进一步考虑不完全维修情形的基础上,采用视情维修策略建立了多状态竞争失效系统的维修模型,提出了系统维修策略的优化问题,实现了更新周期内期望成本率的最小化。本文的创新点在于:（1）为构建更精确的竞争失效系统可靠性模型,将到达系统的冲击分为三类,并采用Copula方法处理多个退化过程之间的相关性。本文所提建模方法,提高了竞争失效系统可靠性模型的精确度;（2）针对定期维修所存在的维修不足或维修过剩的问题,本文采用视情维修策略,建立了竞争失效系统的维修模型,通过优化所建立的维修模型,可得到最优的维修策略,该策略可达到节约维修成本的目的;（3）针对多状态竞争失效系统,本文分别采用延迟时间模型和齐次泊松过程刻画其退化过程和冲击过程,进而建立了系统的维修模型。进一步,考虑到检测误差（不完全检测）和维修度（不完全维修）,对系统的维修模型进行了重新构建,所构建的维修模型可适用于不同工作情境下的多状态竞争失效系统。

The development of science and technology makes the system become more and more complex, systems with protective auxiliary component are common in engineering industry. When the auxiliary components fail, it will not only weaken the ability to protect the main parts, but also affect the state of the remaining operational auxiliary components. However, the structure and dependence between the auxiliary components are often overlooked, which is very important in real operation. In this paper, we studied a system consisting of a main component and a protective auxiliary subsystem, the latter is a load-sharing k-out-of-n system. Since the dependence between main and auxiliary components, as well as between auxiliary components, so it is important to find the failure state of the auxiliary components in time and take the corresponding maintenance strategy. The opportunistic inspection and periodic inspection are proposed in this model. A semi-regenerative process is used to calculate the long-run average cost, based on which the optimal inspection period of the auxiliary subsystem is derived by an enumeration method. © 2022 IEEE.

For multi-component systems, components can be classified according to the impact of component failures: failures of the main component cause the system failures, while failures of the auxiliary component cannot be directly detectable and may put the system at some risk. In this paper, we study a system equipped with main and auxiliary components, and what differs this paper from previous studies on maintenance strategies for such systems is that, we consider not only the failure dependence between components due to the protective effect of the auxiliary component, but also the complex scenario where the system operates in dynamically evolving environments. Environmental evolution results in variations of failure rates of the auxiliary component and some dynamic negative impacts on degradation of the main component. Since hidden auxiliary component failures can only be found by inspection, we consider periodic inspection and opportunistic inspection of the auxiliary component in developing the maintenance strategy. Then we model the system operation by using a semi-regenerative process to obtain the long-run average cost, and minimize the long-run average cost using the inspection period τ as an optimizable decision variable. © 2022 IEEE.

To maintain a multi-component system, different dedicated service teams with different skill sets and tools are often involved. Such a relationship constitutes maintenance team coalition. In most cases, it may not be the best to plan each team's maintenance activities independently as such independent decisions may not achieve the required system-level reliability performance (RP). To balance the reliability and costs of components in achieving a high level of system RP, an efficient method is to assign a failure penalty cost to each maintenance team and then develop their optimal maintenance policy. In this article, the Shapley value is utilized for fair penalty costs allocation to avoid any interest for teams to secede the coalition, whose actual role is to evaluate the criticality level of each component in the context of coalition. Moreover, imperfect inspection and imperfect repair are quite common in practice because of limited resources, technologies and time. To address these practical concerns, a new reliability-centered hybrid preventive maintenance policy is proposed. The optimal inspection interval and age-based replacement interval are determined for each team to minimize the cost rate over an infinite time horizon. Several numerical examples illustrate that the proposed decision-making method is effective in handling such complex maintenance problems involving a coalition of dedicated maintenance teams.